Cyfrifiadureg / Computer Sciencehttp://hdl.handle.net/2160/52015-03-03T20:24:16Z2015-03-03T20:24:16ZOn the reduction of raw image data in the context of the appearance-based approach to robot navigationFrédéricMartinMarkhttp://hdl.handle.net/2160/265872015-01-08T12:19:18Z2010-08-01T00:00:00ZOn the reduction of raw image data in the context of the appearance-based approach to robot navigation
Frédéric; Martin; Mark
The appearance-based approach towards robot navigation is based on a pixel-wise comparison of images. Recent research has shown that the Euclidean distance in image space provides a robust method for robot homing, navigation along routes and topological mapping. The objective of this paper is to investigate how image data can be reduced in order to minimise the computational cost for the image distance calculation without loosing the robustness of the method. A simple 1-D scenario is used to test three different types of reduction methods: one focuses on specific and predefined image regions, one uses fractal sets, while the last is based on a stochastic process. We show that with less than 10% of the data a similar performance can be achieved with the stochastic method, which is then used on a real case study (the visual compass) to assess its performance in a real situation.
2010-08-01T00:00:00ZEfficient image-based tracking of apparently changing moving targetsJamesAndrewFrédérichttp://hdl.handle.net/2160/265862015-01-08T12:19:17Z2009-09-01T00:00:00ZEfficient image-based tracking of apparently changing moving targets
James; Andrew; Frédéric
In this paper, we present an efficient way of representing and tracking a moving object in images. In our approach, the object is visually represented as a set of pixels corresponding to an ideal view of the object as seen by a camera. As the object moves, its appearance can change in a number of ways, depending on the application. In this paper, we present two applications: leader-follower formation and visual guidance from a 'camera in the sky'. In these two applications, the object translates in the column and row directions of the images as well as, respectively, changes in size and orientation. However, other transformations, such as skewing and shearing, could be used in the proposed framework. We present results of real experiments performed in our Lab and show that even on low specification computers, the method performs well and fast enough.
2009-09-01T00:00:00ZThe PDE surface method in higher dimensionsAlanHassanFrédérichttp://hdl.handle.net/2160/265852015-01-08T12:19:16Z2007-09-01T00:00:00ZThe PDE surface method in higher dimensions
Alan; Hassan; Frédéric
This paper presents a method to extend PDE surfaces to high dimensional spaces. We review a common existing analytic solution, and show how it can be used straightforwardly to increase the dimension of the space the surface is embedded within. We then further develop a numerical scheme suitable for increasing the number of variables that parametrise the surface, and investigate some of the properties of this solution with a view to future work.
2007-09-01T00:00:00ZThe visual compass: performance and limitations of an appearance-based methodFrédérichttp://hdl.handle.net/2160/265702015-01-08T11:55:41Z2006-10-01T00:00:00ZThe visual compass: performance and limitations of an appearance-based method
Frédéric
In this article we present an algorithm to estimate the orientation of a robot relative to an orientation specified at the beginning of the process. This is done by computing the rotation of the robot between successive panoramic images, grabbed on the robot while it moves, using a subsymbolic method to match the images. The context of the work is Simultaneous Localization And Mapping (SLAM) in unstructured and unmodified environments. As such, very few assumptions are made about the environment and the robot's displacement. The algorithm's performance depends on the value of a number of parameters being determined to provide overall good performance of the system. The performance is evaluated in different situations (trajectories and environments) with the same parameters and the results show that the method performs adequately for its intended use. In particular, the error is shown to be drifting slowly, in fact much slower than unprocessed inertial sensors, thus only requiring infrequent realignment, for example when relocalizing in a topological map. Limitations of the proposed methods are also shown and discussed.
2006-10-01T00:00:00Z